The U.S. Geological Survey (USGS) maintains shoreline positions for the United States' coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release, and other associated products, represent an expansion of the USGS national-scale shoreline database to include Puerto Rico and its islands, Vieques and Culebra. The USGS, in cooperation with the Coastal Research and Planning Institute of Puerto Rico—part of the Graduate School of Planning at the University of Puerto Rico, Rio Piedras Campus—has derived and compiled a database of historical shoreline positions using a variety of methods. These historical shoreline data are then used to measure the rate of shoreline change over time. Rate calculations are computed within a geographic information system (GIS) using the DSAS version 5.1 software. Starting from a user defined baseline, measurement transects are created by DSAS that intersect the shoreline vectors. The resulting intersections provide the location and time information necessary to calculate rates of shoreline change. The overall project contains shorelines, baselines, shoreline change rates (long-term and short-term), and shoreline intersects (long-term and short-term), for Puerto Rico, and the adjacent islands of Vieques and Culebra.

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

This dataverse contains two files: One (MIT_Supercloud_Datacenter_Model.7z) containing the bottom-up model for resource allocation, and another file (Datacenter_Flexibility_Project_Revised.7z) containing per-job power consumption profiles for batch workloads to generate batch-only data center power profiles.

Abstract

The Cox’s Bazar Panel Survey (CBPS) was completed in August 2019, through a partnership between the Yale Macmillan Center Program on Refugees, Forced Displacement, and Humanitarian Responses (Yale Macmillan PRFDHR), the Gender & Adolescence: Global Evidence (GAGE) program, the Poverty and Equity Global Practice of the World Bank and the State and Peacebuilding Fund (SPF) administered by the World Bank. It is a representative survey of the post-2017 population of displaced Rohingya and households in host communities in the Cox’s Bazar district in Bangladesh.

The high-frequency phone tracking (HFT) surveys were built to maintain communication with baseline respondents while collecting rapid data on key welfare indicators on labor, basic needs and education. Three rounds of the HFT have been completed between 2020-2021, which have been used to produce welfare updates on the host and Rohingya population residing in Cox's Bazar, Bangladesh, particularly amidst the COVID-19 crisis.

The tracking surveys collected information across three broad welfare dimensions: labor, access to basic needs and education status of school-aged children. Round 1 collected information on labor and access to basic needs only; the module on education was added Round 2 onwards.

Geographic coverage

Cox's Bazar district and some parts of Bandarban district.

Analysis unit

Households and individuals

Universe

a) Rohingya population living in camps and b) host population within Cox's Bazar and Bandarban district.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CBPS study has a total sample size of 5,020 households (HHs), divided among three strata covering Rohingya refugees in camps and host communities in Cox’s Bazar district and some adjacent regions of Bandarban district. The CBPS HFT attempted to follow the full baseline sample of 5,020 household in each round, with no alterations or additions made to the sampling design. The baseline sampling strategy is detailed below. The three strata are defined as:
i. Rohingya refugees in camps ii. High exposure hosts: hosts within 15 km (3-hour walking distance) of camps iii. Low exposure hosts: hosts at more than 15 km (3-hour walking distance) from camps (In the datasets, the 'settlement_type' and 'stratum' variables identify the different levels at which the sample is representative)

Defining the camp strata: A two-step data collection on Rohingya refugee prevalence within host communities (i.e., outside of camps) confirmed that prevalence in host communities was low, and that this was the case not only for newer Rohingya displaced, but for the older cohort of displaced, as well. This pattern of refugee prevalence supported having one stratum for the Rohingya displaced living in camps. The sampling strategy for the CBPS therefore focused on generating representative estimates for the camp based Rohingya population in Cox’s Bazar district.

Defining the host strata: For hosts, the sampling strategy was designed to account for the differential implications of a camp-based concentration of close to a million Rohingya displaced for different areas of Cox’s Bazar. To distinguish between host communities that are differentially affected by the arrival of the Rohingya, the CBPS sampling strategy used a threshold of three hours’ walking time from a campsite to define two survey strata: (i) host communities with potentially high exposure (HE) to the displaced Rohingya, and (ii) host communities with potentially low exposure (LE).

Sampling frame: The camp sample uses the Needs and Population Monitoring Round 12 (NPM12) data from the International Organization for Migration as the sampling frame. For the host sample, a combination of the 2011 population census, Admin 4 shapefiles from the Bureau of Statistics and publicly available Google Earth imagery and OpenStreetMaps were used to develop a sampling frame.

Stages of sample selection: For camps, NPM12 divided all camps into 1,954 majhee blocks.1 200 blocks were randomly selected using a probability proportional to the size of the camp. A full listing was carried out in each selected camp block.

For hosts, a two-stage sampling strategy was followed. The first stage of selection was done at the mauza level by strata. A random sample of 66 mauzas was drawn from a frame of 286 mauzas using probability proportional to size. Based on census population size, each mauza was divided into segments of roughly 100-150 households. The second stage selected three segments from each selected mauza with equal probability of selection.

Listing and replacements: Within each selected PSU in camps (blocks) and hosts (mauza-segments), all households (100-150 on average) were listed. Of listed households, 13 households were selected at random for interview, with an additional replacement list of 5 households. More information on the sampling strategy and process can be found on the published working paper titled “Data Triangulation Strategies to Design a Representative Household Survey of Hosts and Rohingya Displaced in Cox’s Bazar, Bangladesh”.

Sampling deviation

While the original sampling strategy was designed to be representative of all camp-based Rohingya displaced, campsites with older Rohingya displaced refused to participate in the listing due to other political sensitivities. This refusal was maintained despite many attempts. Since the older Rohingya displaced were not a separate stratum, a decision was made to drop these households from the survey. Therefore, the attained sample does not contain registered refugees from the two camps – Kutupalong RC and Nayapara RC.

The host sample covers six out of eight upazilas in Cox’s Bazar District (Chakaria, Cox’s Bazar Sadar, Pekua, Ramu, Teknaf, and Ukhia upazilas) and one upazila in Bandarban District (Naikhongchhori upazila). The two upazilas not covered within the sample are the islands of Kutubdia and Maheshkhali.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The R1 tracking questionnaire was developed as a lean version of the questionnaire implemented during the CBPS baseline. The R2 and R3 questionnaires retained certain aspects of the R1 questionnaire, but also added more detailed questions on aspects such as food security (in consultation with UN-WFP) and credit-seeking and coping behavior based on findings observed in previous rounds and dynamic research needs within the COVID-19 crisis.

One questionnaire was developed per round of data collection with modules containing household level questions on access to basic needs, credit-seeking behavior, access to health services, vaccinations and individual level questions on labor market status. Any adult, knowledgeable member of the confirmed sample household were eligible to answer the household modules. The labor module was only permitted if the respondent reached was any one of the 2-3 selected adults within the household who had completed the baseline adult questionnaires.

Questionnaires were developed in English and translated into Bengali. The translations to Bengali were thoroughly reviewed by the World Bank team’s local consultants to ensure quality. Pretesting and piloting were done using the Bengali questionnaires.

All questionnaires and modules in English are provided as external resources.

Cleaning operations

Data was collected through computer-assisted telephone interviews via SurveyCTO, an ODK-based platform. Maintenance of correct questionnaire flow was ensured through in-built skips and logic checks within the programmed questionnaire.

No manual data corrections were made on submitted interviews by the data processing team. Interviews flagged as needing field corrections due to mistaken entries were re-submitted by enumerators upon strict evaluation by the project team upon close review of the concerns raised and filtered by the program automatically before closing of data collection in each round.

In addition to logic checks within the survey program itself, extensive data consistency checks and quality indicators were developed by the WB team to monitor data quality during survey implementation. Field debriefs were held frequently during the piloting phase and first week of data collection, and once a week in latter weeks to provide feedback to enumerators and gain clarity on data quality concerns.

Post data collection, structural and consistency checks have been conducted on each round dataset and in-between datasets from different rounds.

Response rate

The response rates at household level for each round of the CBPS HFT, based on the baseline sample of 5,020 and disaggregated at stratum-level are: Round 1: Overall - 67%; Camps - 54%; High exposure: 71%; Low exposure: 72% Round 2: Overall - 72%; Camps - 63%; High exposure: 81%; Low exposure: 80% Round 3: Overall - 68%; Camps - 55%; High exposure: 81%; Low exposure: 80%

*Note that the Round 1 tracking exercise was a joint-effort between the Yale Y-Rise team and the WB team. The Yale team contacted and surveyed a randomly selected 25% of baseline households, while the WB team completed the remaining 75%. The Round 1 dataset contains data on this segment of the sample only as the welfare surveys implemented by the teams were different.

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section.

The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems.

Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments.

Method Step Description:

1. Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed.

2. Image analysis: A photo image analysis method with sequence (moving images) was used for the occurrence data extraction and organism counts; measurements were taken to obtain vegetation cover percentages and substrate analyzes were also carried out. Analyzes were performed with the open-source Fiji software from ImageJ. A quality/visibility rating was assigned to the analyzed image sequences.

3. Taxonomic approach: Epibenthic organisms were identified at the lowest possible taxonomic rank. A morphotype approach has been systematically used (during annotations) for the identification of sponges, hydrozoans and bryozoans, and occasionally for other organisms such as algae. Species codes were also used to distinguish certain species that could not be identified at the time of the annotations (see verbatim Identification). To eliminate observer bias, the same person analyzed all images used in this database. The organisms were identified from underwater images using a combination of identification guides and scientific papers.

4. Open nomenclature: The concept of open nomenclature has been integrated into occurrence data to support taxonomic identifications with their level of certainty, as recommended by Horton et al., 2021. The abbreviation stet. (stetit) was used when the decision not to go lower was made but an identification might be possible, whereas indet (Indeterminabilis) was used when a lower level identification was considered uncertain or impossible (see identificationqualifier). In addition, the abbreviation Confer (cf.) was used and integrated into the data tables (see occurrenceRemarks) in order to link identifications that could potentially and/or possibly be associated.

5. Remarks: Several remarks have also been incorporated (see organismRemarks, identificationRemarks and taxonRemarks), and are intended to provide additional information that may be useful to some data users; Please note that these sections could be modified or improved.

6. Quality control: The taxonomic identifications were verified through a validation process, in collaboration with various expert taxonomists. All scientific names have been checked against the World Register of Marine Species (WoRMS) to match currently recognized standards. The WoRMS match was placed in the taxonID field of the instance file. Data quality control was performed using Robistools and worms packages. All sample locations were plotted on a map for visual verification that the latitude and longitude coordinates were within the described sample area.

7. Data sharing: Only metadata and biodiversity occurrence data are shared in this dataset. The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event" file includes generic event information, including date and location. The "occurrence" file includes the original identifiers of the observed organisms, identification comments and their taxonomy. A data dictionary is also provided to explain the fields used. For access to other data or images, contact David Lévesque.

For more details about the project and the methodology, a technical report (Scallon-Chouinard et al., 2022) including sampling methods with drop camera photo systems (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs) is currently available online (https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41081225.pdf); another technical report detailing photo and video image analysis methods will also be available.

This project is part of the Coastal Environmental Baseline Program under the Oceans Protection Plan of Fisheries and Oceans Canada.

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section. The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems. Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments. Method Step Description: Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed.

Aim: We modeled isoscapes in the Northeast Pacific using satellite-based data with the main objective of testing if isoscapes defined by a few key parameters can be used as a proxy for secondary productivity.

Location: Northeast (NE) Pacific; 46 – 60⁰N and 125 – 165⁰W.

Time period: From 1998 to 2017 (ongoing).

Major taxa studied: Zooplankton with a focus on large herbivores.

Methods: Approximately 280 summer zooplankton samples were analyzed for Carbon (δ13C) and Nitrogen (δ15N) stable isotope (SI) ratios. Environmental conditions experienced by zooplankton organisms were extracted from satellite, in situ sensor and model databases. A generalized additive model approach was used to explain the spatial variability of δ13C and δ15N values and predict isoscapes.

Results: Sea surface temperature (SST), sea level anomaly (SLA) and chlorophyll-a concentration emerged as the significant SI predictors. Modelled isoscapes reproduced patterns observed in δ13C and δ15N value distribution, such as a decrease from the coast to offshore. The contribution of eddies in enhancing local production in the open ocean was also well captured by the models. In the central part of the NE Pacific higher SI values were correlated with higher large copepod biomass measured by the North Pacific Continuous Plankton Recorder (CPR) survey. However, in the area off the coast of British Columbia (BC) high δ15N variability appeared to be associated with episodic intrusions of coastal waters demonstrating that caution is needed when interpreting sharp changes in SI ratios.

Main conclusions: While the mechanisms driving SI ratio variability are complex, we demonstrated that a few parameters used as a proxy for some of these major mechanisms are able to successfully produce isoscape models. This approach was proven useful to provide a qualitative estimate of the secondary production, which can be particularly valuable in a region where few data are available.

Methods Approximately 280 summer zooplankton samples were analyzed for Carbon (δ13C) and Nitrogen (δ15N) stable isotope (SI) ratios. Environmental conditions experienced by zooplankton organisms were extracted from satellite, in situ sensor and model databases. A generalized additive model approach was used to explain the spatial variability of δ13C and δ15N values and predict isoscapes.

This dataset derives from a series of beam trawl tows conducted during several research surveys in coastal areas of the St. Lawrence Estuary, between Portneuf-sur-Mer and Pointe-des-Monts, and between June and October of 2019, 2020, 2021 and 2022. It contains catch data for fish and invertebrates (occurrence and catch weights by species), in trawl tows conducted at depths ranging from 10 to 50 meters. Data were collected in various cruises: • June 28th to July 5th 2019 (NGCC Leim) • September 30th to October 9th 2019 (NGCC Leim) • October 1st to October 10th 2020 (NGCC Leim) • April 22nd to May 5th 2021 (NGCC Perley) • October 15th to October 24th 2021 (NGCC Perley) • June 24th to July 15th 2022 (NGCC LEIM) The beam trawl used to generate this data set consists of a frame (width of 2.8 m, height of 0.8 m) equipped with a 6.5 m long net with 40 mm diamond mesh, which is lined with a net (skirt) of square mesh (5 mm) at the cod-end (length 2 m) and a protective apron (75 mm mesh) on the ventral portion. Three skid chains are linked at the base of the skates. Each station corresponds to a 5 to 10 minutes tow along an isobath at a speed of about 2 knots. At each haul, the trawl catch was placed on a sorting table on the deck and the organisms were sorted and identified at the best possible taxonomic resolution. Most taxa were independently weighed. Some invertebrates taxa were subsampled, counted and weighted in order to estimate their contribution (weight and number) to the total catch. Additionally, the first 30 fish of each species were measured and weighed individually. Taxonomic names were verified on the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match has been put in the scientificNameID field in the occurrence file. Data quality control was performed using the R packages obistools and worrms. All sampling locations were plotted on a map to perform a visual check confirming that the latitude and longitude coordinates were within the described sampling area. Data acquired during the research surveys additionally included: 1) occurrence data on epibenthic invertebrates and submerged aquatic vegetation in photo samples from a drop camera system, 2) occurrence data on fish and invertebrate taxa in video samples collected using a baited underwater video system (BUV), 3) substrate classification based on drop camera photo samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The first two items are available as independent data on the OBIS portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aimed to acquire environmental baseline data contributing to the characterization of important coastal areas and in support of evidence-based assessments and management decision-making for preserving marine ecosystems. Which contribute to the elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary between Portneuf-sur-Mer and Godbout (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as dropped photo cameras and stereoscopic baited video camera systems. The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments. This project was funded by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan.

The National Renewable Energy Laboratory (NREL) was tasked with developing a metric in 2012 to measure the impacts of RD&D funding on the cost and time required for geothermal exploration activities. The development of this cost and time metric included collecting cost and time data for exploration techniques, creating a baseline suite of exploration techniques to which future exploration cost and time improvements can be compared, and developing an online tool for graphically showing potential project impacts (all available at http://en.openei.org/wiki/Gateway: Geothermal). This paper describes the methodology used to define the baseline exploration suite of techniques (baseline), as well as the approach that was used to create the cost and time data set that populates the baseline. The resulting product, an online tool for measuring impact, and the aggregated cost and time data are available on the Open Energy Information website (OpenEI, http://en.openei.org) for public access.

BackgroundSoil-transmitted helminths (STHs) and mutualistic gut microbes coexist in the gastrointestinal tract. However, limited data exist regarding how STH infections are associated with gut microbiome profiles.MethodWe conducted a cross-sectional analysis of baseline data collected in a longitudinal study to identify and explain differences in microbial communities between STH-infected and non-infected Ethiopian school children. We collected 138 stool samples and analyzed them for STH infection using standard direct wet mount and Kato Katz methods. The gut microbiome profiles were characterized using targeted amplicon sequencing of the 16S rRNA gene from the total DNA extracted from the stools.ResultsChildren infected with Trichuris trichiura showed significantly lower microbial diversity than those who were non-infected (p

The vast majority of SARS-CoV-2 infections are uncomplicated and do not require hospitalization, but these infections contribute to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of virologic and clinical outcomes in planning future treatment studies of COVID-19. We recently completed a randomized clinical trial of Pegylated PegIinterferon Lambda for treatment of SARS-CoV-2 infected patients conducted in the Stanford COVID-19 CTRU. Leveraging longitudinal samples and data from this trial, we define early immunebaseline and infection-induced signatures that predict the duration of viral shedding, resolution of symptoms, and immunologic memory. We recruited 108 subjects between age 18 to 75 who are PCR positive for SARS-CoV-2. The subjects were randomized to receive a single dose of Peginterferon Lambda or placebo at their first visit (day 0). In-person follow-up visits were conducted on Day 1, 3, 5, 7, 10, 14, 21, and 28, with the assessment of symptoms and vitals and collection of oropharyngeal swabs for SARS-CoV-2 testing. To profile the immune response in the COVID-19 patients, we conducted RNA-sequencing assays using blood samples collected at day 0 and day 5 after enrollment.

Abstract

The Hunger Safety Net Programme (HSNP) is a social protection project being conducted in the Arid and Semi-Arid Lands (ASALs) of northern Kenya. The pilot phase has now concluded and the HSNP is beginning to scale up under Phase 2. The ASALs are extremely food-insecure areas highly prone to drought, which have experienced recurrent food crises and food aid responses for decades. The HSNP is intended to reduce dependency on emergency food aid by sustainably strengthening livelihoods through cash transfers.

Oxford Policy Management was responsible for the monitoring and evaluation (M&E) of the programme under the pilot phase, with the intention of informing programme scale-up as well as the government’s social protection strategy more generally. The M&E involved a large-scale rigorous community-randomised controlled impact evaluation household survey, assessment of targeting performance of three alternative targeting mechanisms (Social Pension; Dependency Ratio; Community-based Targeting), qualitative research (interviews and focus group discussions) to assess targeting and impact issues less easily captured in the quantitative survey, and on-going operational and payments monitoring to ensure the smooth implementation of the programme. Findings were communicated to the HSNP Secretariat, Government of Kenya and the Department for International Development (DFID) on a regular basis to inform and advise on policy revisions and development. The M&E component used the data it produced to advise the design of HSNP Phase 2, including micro-simulations of different programme targeting scenarios and review of the phase 2 targeting approach which combines proxy means testing with community-based targeting.

The impact evaluation study compares the situation of HSNP and control households at the time of their selection into the programme (baseline), with their situation 12 months (year 1 follow-up) and 24 months later (year 2 follow-up). Over this 24-month period most of the HSNP households covered by the evaluation had received 11 or 12 bi-monthly transfers (initially KES 2,150, increased to KES 3,500 by the end of the evaluation period).

The baseline data collection was completed in November 2010, the first round of follow-up data collection finished in November 2011, and the final round of fieldwork - in November 2012.

Geographic coverage

Counties of Turkana, Marsabit, Wajir, and Mandera.

Analysis unit

• individuals,
• households,
• community.

Universe

All persons living within "secure" sub-locations across all counties at the time of sampling (2008; due to sporadic insecurity across the four counties, a small portion of sub-locations were deemed to be insecure when the sample was drawn and so excluded from the sample frame).

Kind of data

Sample survey data [ssd]

Sampling procedure

At follow-up 2, in addition to attrition, the sample size is further reduced because the follow-up 2 survey covered eight fewer sub-locations, 40 rather than 48. Overall 2,436 households were surveyed (at the baseline, 5,108 households were covered).

The evaluation sub-locations were selected from a sample frame of all secure sub-locations in each district. In each district 12 sub-locations were selected with PPS (Probability Proportional to Size) with implicit stratification by population density such that there is an even number of selected sub-locations per new district.

The evaluation sub-locations were sorted within districts by population density and paired up, with one of the pair being control and one being treatment. The sampling strategy for the quantitative survey was designed in order to enable a comparison of the relative targeting performance of three different targeting mechanisms. These are:

• Community-based targeting (CBT): The community collectively selected households they consider most in need of transfers, up to a quota of 50% of all households in the community;
• Dependency ratio targeting (DR): Households were selected if individuals under 18 years old, over 55 years old, disabled or chronically ill made up more than a specified proportion of all household members;
• Social pension (SP): All individuals aged 55 or older were selected.

For both the treatment and control sub-locations there are an equal number of CBT, SP and DR sub-locations. Assignment of targeting mechanisms to sub-locations was done randomly across the same pairs that were defined to assign treatment and control status. In all the evaluation sub-locations, the HSNP Admin component implemented the targeting process. In half the sub-locations the selected recipients started receiving the transfer as soon as they were enrolled on the programme - these are referred to as the treatment sub-locations. In the other half of the evaluation sub-locations, the selected recipients were not to receive the transfer for the first two years after enrolment - these are referred to as the control sub-locations.

The households in the treatment sub-locations that are selected for the programme are referred to as the treatment group. These households are beneficiaries of the programme. In control sub-locations the households that are selected for the programme are referred to as the control group. These households are also beneficiaries of the programme but only begin to receive payments two years after registration. The targeting process was identical in the treatment and control sub-locations. The following population groups can thus be identified and sampled: - Group A: Households in the treatment sub-locations selected for inclusion in the programme; - Group B: Households in control sub-locations selected for inclusion in the programme but with delayed payments; - Group C: Households in treatment sub-locations that were not selected for inclusion in the programme; - Group D: Households in control sub-locations that were not selected for inclusion in the programme.

Because targeting was conducted in both treatment and control areas, households were sampled in the same way across treatment and control areas. Selected households (groups A and B) were sampled from HSNP administrative records. Sixty six beneficiary households were sampled using simple random sampling (SRS) in each sub-location (in two of sub-locations this was not possible due to insufficient numbers of beneficiaries in the programme records). In cases of household non-response replacements were randomly drawn from the remaining list of non-sampled households. This process was strictly controlled by the District Team Leaders.

Non-selected households (groups C and D) were sampled from household listings undertaken in a sample of three settlements within each sub-location. These settlements were randomly sampled. The settlement sample was stratified by settlement type, with one settlement of each type being sampled. Settlements were stratified into three different types: 1. Main settlement (the main settlement was defined as the main permanent settlement in the sub-location, often known as the sub-location centre and usually where the sub-location chief was based. As there was always one main settlement by definition, the main settlement was thereby always selected with certainty). 2. Permanent settlements (permanent settlement is defined as a collection of dwellings where at least some households are always resident, and/or there is at least one permanent structure). 3. Non-permanent settlements.

As concern community level data, community questionnaires were conducted in every community for which at least one household interview was attached. A community was defined as a settlement or a sub-section of a settlement if that settlement had been segmented due to its size. Due to missing data, a small proportion of households are not linked to any community data.

The above explanation is taken from "Kenya HSNP Monitoring and Evaluation Component: Impact Evaluation Final Report 2009 to 2012". For more details please refer to this report in Related Materials section.

Sampling deviation

The reduction in the number of sub-locations surveyed at follow-up 2 was the result of decisions made by the programme and its stakeholders, rather than a technical decision by the evaluation team. This reduction in sample size is unfortunate for a number of reasons. Firstly, it undermines the study design to the extent that the smaller sample size reduces the ability to detect impact with statistical significance. Secondly, it affects the balance of the sample, meaning that treatment and control populations are less balanced at baseline than they were with the original sample structure. Lastly, the sample was designed to be seasonally balanced across the whole calendar year, which is no longer the case as sub-locations that would have been surveyed in the latter and early part of the calendar were dropped. Another implication of the reduced sample at follow-up 2 is that the baseline estimates presented in this report differ from those presented in the baseline and follow-up 1 impact reports. This is because the estimates now relate to slightly different populations.

Mode of data collection

Computer Assisted Personal Interview [capi]

This paper describes the methodology used to define the baseline exploration suite of techniques (baseline), as well as the approach that was used to create the cost and time data set that populates the baseline. The resulting product, an online tool for measuring impact, and the aggregated cost and time data are available on the Open Energy Information website (OpenEI, http://en.openei.org) for public access. The Department of Energy's Geothermal Technology Office (GTO) provides RD&D funding for geothermal exploration technologies with the goal of lowering the risks and costs of geothermal development and exploration. The National Renewable Energy Laboratory (NREL) developed this cost and time metric included collecting cost and time data for exploration techniques, creating a baseline suite of exploration techniques to which future exploration cost and time improvements can be compared, and developing an online tool for graphically showing potential project impacts (all available at http://en.openei.org/wiki/Gateway: Geothermal).

The pedunculopontine tegmental nucleus of the brainstem (PPTg) has extensive interconnections and neuronal-behavioural correlates. It is implicated in movement control and sensorimotor integration. We investigated whether single neuron activity in freely moving rats is correlated with components of skilled forelimb movement and whether individual neurons respond to both motor and sensory events. We found that individual PPTg neurons showed changes in firing rate at different times during the reach. This type of temporally specific modulation is like activity seen elsewhere in voluntary movement control circuits, such as the motor cortex, and suggests that PPTg neural activity is related to different specific events occurring during the reach. In particular, many neuronal modulations were time-locked to the end of the extension phase of the reach, when fine distal movements related to food grasping occur, indicating strong engagement of PPTg in this phase of skilled individual forelimb movements. In addition, some neurons showed brief periods of apparent oscillatory firing in the theta range at specific phases of the reach-to-grasp movement. When movement-related neurons were tested with tone stimuli, many also responded to this auditory input, allowing for sensorimotor integration at the cellular level. Together, these data extend the concept of the PPTg as an integrative structure in the generation of complex movements, by showing that this function extends to the highly coordinated control of the forelimb during skilled reach to grasp movement and that sensory and motor-related information converges on a single neuron, allowing for direct integration at the cellular level. Methods All procedures were approved by the University of Otago Committee on Ethics in Care and Use of Laboratory Animals and were in accord with the “Principles of Laboratory Animal Care” (National Institutes of Health publication number 80-23, revised 1996). The behavioural and single-neuron recording methods have been previously described in detail (Hyland & Jordan, 1997; Parr-Brownlie & Hyland, 2005). Male Wistar rats (~ 400 g at the time of surgery) were trained to reach into a 25-mm-wide, 14-mm high rectangular opening 55 mm above the floor to retrieve chocolate flavoured breakfast cereal (Coco Pops™) from a tray. Once a clear paw preference for reaching had been established, chronic extracellular recording electrodes were implanted into the contralateral PPTg (anteroposterior -7.8 mm and lateral ± 2.0 mm, relative to bregma (Paxinos & Watson, 1997)) using sterile stereotaxic technique under full anaesthesia. During recording sessions, signals from electrodes were amplified and filtered (2000 -8000 x, 0.5 - 10 kHz bandpass). Extracellular action potentials from single neurons were recorded, along with marker channels for automatically or manually entered behavioural events using SciWorks software (Datawave, CO). When a suitably isolated neuron was identified, it was first recorded while animals made ~ 50 reaches. Following this, for a subset of neurons recordings were made while the rats were exposed to 50 trials of 50 ms duration 4.5 kHz tone stimuli (Med Associates Sonalert), with pseudorandom intertrial intervals.
Unit activity was analysed off-line using Spike2 software (CED, Cambridge, UK). Spikes belonging to single neurons were discriminated based on waveform shape (Fig. 1 B). For analysis of reach- and tone responses, activity was averaged over the reaching trials or tone presentations in peri-event time histograms (PETH). For reach data, PETH was centred on the interruption of an infrared beam at the position of the food. We chose this moment in the reach sequence because we were interested in determining if PPTg activity may correlate to distal skilled components of the reach-to-grasp movement, and this marks the termination of the extension phase and onset of the complex movements of the paw that are generated for grasping (Whishaw & Pellis, 1990; Hyland & Jordan, 1997; Sacrey et al., 2009). For the reach-PETH, cell activity was averaged across trials, extending for 2 seconds before and after the light-beam interrupts generated by the preferred paw (contra-lateral to the recorded hemisphere) and normalised by converting to instantaneous frequency (spikes/s) (Fig. 1 C). The first 500 ms of each PETH was used to define the baseline firing rate. PETH for slow-firing cells used 50 ms bin width and for fast-firing cells, 25 ms was used. Peaks in the PETH were defined as a group of consecutive bins that were beyond + 2 standard deviations (SD) from the mean baseline firing rate. For fast-firing cells, three consecutive 25ms bins were required, for slow-firing cells, two 50 ms bins. For inhibitions, the same criteria were applied using a threshold at – 2 SD, except for cases in low-firing cells where this threshold value was < 0 spikes/s. In these, we used the criterion defined by Galvan et al. (2016), where troughs were defined as periods in the PETH with zero bin counts that lasted ≥ 2 bins longer than any silent period in the baseline. The time of the modulation onset was defined as the leading edge of the first bin to cross the threshold, and the duration measured to the trailing edge of the last bin remained beyond the threshold. Onset times are expressed relative to the time of the light-beam interrupt which marked both the end of the ballistic extension phase of the reach and the onset of grasping. The amplitude of peaks was quantified as the mean of the in-peak bins. For analysis of firing patterns, autocorrelation histograms were calculated from selected periods around or between reaching events. For tone response PETH, similar methods were used except that the PETH was centred on the onset of the tone and a 2 ms bin width was used to capture the onset time of the short latency responses. Statistical analyses were performed using GraphPad Prism Version 8 (GraphPad Software LLC). To assist in the demarcation of the timing of overall population responses separately for 1st (+) and 1st (-) responses we performed a boxcar analysis on the average normalized Z-score in 50 ms bins using one-sample t-tests to determine deviation from baseline (Z = 0), over the period – 2 to + 1.5 s (n = 71 bins), with overall alpha = 0.05. Bonferroni correction for multiple comparisons (p = alpha/n) yielded p = 0.0007 to reject the null hypothesis. We therefore set p = 0.0001 as a conservative threshold to define a significant population-level response. To mark the onset and offset times for such responses we used the time at which p values crossed 0.001 before and after reaching the threshold. To test whether the timing of onset of the population (+) and (-) response components might differ, we performed a two-factor repeated measures ANOVA for individual neuron’s original (unsmoothed) PETH bin data for the factors RESPONSE TYPE (+, -) and TIME (71 time points from -2 to 1.5 s). To account for variation in baseline firing rate between neurons, data were normalised by calculating Z-score values for each PETH bin as the difference between the bin firing rate and the mean baseline rate (-2 to -1.5 s), divided by the standard deviation of the baseline rate. For 1st (-) neurons Z-score values were inverted so that the analysis focussed on each group’s deviation from 0, rather than the sign of the response. Sphericity was not assumed, with Geisser-Greenhouse correction as required. To objectively quantify the instantaneous frequency of regular repeated peaks in PETH and autocorrelation histograms we used the Fit Data function in Spike2 v7 to fit a sinusoid function to ranges of data that were initially visually selected as potentially containing oscillatory activity. The least-square fitting function minimised the sum of squares of the errors between the data and the fitted curve, and the Spike2 algorithm calculated an estimate of the probability that a minimum sum of squares of errors of at least this size would occur (Spike2 for Windows Manual v7, 2017).

Macroalgae, in particular kelps, produce a large amount of biomass in Kongsfjorden, which is to a great extent released into the water in an annual cycle. As an example, the brown alga Alaria esculenta loses its blade gradually, 3 ± 0.8 % of the blade area per day (August 2012), thereby adding to the pool of particulate organic matter (POM) in the fjord. Upon release small thallus pieces are “aging” in that they are prone to leaching and serving as substrate for microorganisms, thus turning into palatable food for suspension and bottom feeders. In order to define a macroalgal baseline for the Kongsfjorden food web, stable isotopes d14C and d15N were measured in individuals of A. esculenta, Saccharina latissima and Laminaria digitata directly sampled after collection and in artificially produced POM (aPOM) of A. esculenta that was allowed to age under experimental conditions. In aPOM from this species sampled in August 2012 the C/N ratios decreased between d1 and d8 of a 14-day culture period in parallel to the fading photosynthetic activity of the algal fragments as demonstrated by use of an Imaging-PAM. Microscopic observations of the aPOM in August 2012 and 2013 revealed the frequent occurrence of small brown algal endo- and epiphytes. First feeding experiments with Mysis oculata (Mysids) and Hiatella arctica (Bivalves) showed that these species can ingest macroalgal POM. The importance of kelp-derived POM for the food web is subject of the current research.

AbstractClimate change may lead to phenological mismatches, where the timing of critical events between interacting species becomes de-synchronized, with potential negative consequences. Evidence documenting negative impacts on fitness is mixed. The Cushing match-mismatch hypothesis, the most common hypothesis underlying these studies, offers testable assumptions and predictions to determine consequences of phenological mismatch when combined with a pre-climate change baseline. Here, we highlight how improved approaches could rapidly advance mechanistic understanding. We find that currently no study has collected the data required to test this hypothesis well, and 71% of studies fail to define a baseline. Experiments that clearly link timing to fitness and test extremes, integration across approaches, and null models would aid robust predictions of shifts with climate change. MethodsWe located papers relating phenological data from trophic interactions to fitness and/or performance of the consumer and/or the resource by conducting keyword searches in ISI Web of Science published up to June 2017. Keywords included phenolog* AND mismatch* OR synchron* AND interact* AND (fitness* OR performance*). If more than one measure of phenology was included, we chose the one used by the authors to calculate mismatch and examine its impact on performance. Our final review included 42 studies with 45 pair-wise species interactions (3 studies had 2 interactions). Based on the type of data collected for the consumer and resource, we classified studies as life history (i.e. one that collected data at the individual level) or one that collected data at the population or community (i.e., across species). To determine whether studies had the potential to define pre-climate change baselines, we measured the study’s time span and years of data based on the years where phenology data was available for both the consumer and resource, and consumer performance data was available. Usage notesEach observation is an individual pair-wise species interaction.

Proposed modified water deliveries to Indian Tribal Lands, Big Cypress National Preserve, and Water Conservation Area 3A require that flow and nutrient loads at critical points in the interior surface water network be measured. Defining the foundation for water levels, flows, and nutrient loads has become an important baseline for Storm Treatment Area 5 and 6 development, recent C-139 Basin flow re-diversions, and future L-28 Interceptor Canal de-compartmentaliztion including flow rerouting into the Big Cypress Preserve. Flow monitoring for the two primary flow routes for both L-28 Interceptor Canal and L-28 is key to developing this network. Data are available for L-28 Interceptor Canal below S-190, L-28 Canal above S-140, and L-28 Interceptor South .

The accurate determination of flow through the interior canal networks south of Lake Okeechobee and the C-139 basin remains critical for water budgets and regional model calibrations as defined by the Everglades Forever Act of 1994 and due to the Comprehensive Everglades Restoration Plan (CERP) initiative to reroute Big Cypress Preserve flows. The implementation of strategically located stream flow gaging points and associated data collection for nutrients has helped define future surface-water flow requirements and has provided valuable baseline flow data prior to the establishment of the recently constructed northern Storm Treatment Areas (STA’s 5 and 6) and the Rotenberger Wildlife Management Area. Generating continuous flow data at selected impact points for interior basins has complemented the existing eastern coastal canal discharge network, and has allowed for more accurately timed surface-water releases while providing flow and nutrient monitoring after recent STA implementation. A unique multi-agency experiment was conducted with much success with the focus on cooperation and development of new instrumentation and acoustic flow-weight auto-sampler protocols. The original data collection and processing was provided by three separate entities at each site with responsibilities originally allocated between the U.S. Geological Survey (USGS), the Seminole Tribe of Florida, and SFWMD. USGS provides calibration, analysis and processing of acoustic velocity meters (AVM’s) and side-looking Doppler systems and stage shaft encoders, SFWMD provides data loggers with real-time flow-weighted algorithms, and radio frequency (RF) telemetry instrumentation. The Seminole Tribe provides auto-sampler service and funds nutrient load analysis through the USGS Ocala Lab.

Abstract

The benefits of the water and sanitation sub activity will be measured using a rigorous quasi-experimental impact evaluation methodology. An impact evaluation is a study that measures the changes in outcomes that measure aspects of wellbeing which can be attributed to a specific intervention. Impact evaluations require a credible and rigorously defined counterfactual, which estimates what would have happened to the beneficiaries absent the project. Estimated impacts, when contrasted with total related costs, provide an assessment of the intervention's cost-effectiveness.

The evaluator divided the primary evaluation questions in different categories: welfare indicators, coping cost in cash and time, health, education, reliability and quality of service, spillover effects. In addition, we allow for differential impacts in gender and social groups for these main outcomes.

Household welfare o Do water and sanitation infrastructure investments increase household expenditure or income? What factors might explain the impact (or lack of impact) in this area? o What are the consequences of water and sanitation investments for expenditure patterns?

Coping costs and cash expenditure on water o Do water and sanitation interventions reduce coping costs? What factors might explain the impact (or lack of impact) in this area? o Do they reduce cash expenditures on water and on sanitation services? What factors might explain the impact (or lack of impact) in this area?

Health o Do water and sanitation interventions reduce incidence of diarrheal illness? o What factors (hygiene behavior, source and household-level water quality, household source choice) might explain the impact (or lack of impact) in this area?

Education o Do water and sanitation interventions increase school enrollment among children aged 7 to 12? And children age 6 to 18? What factors might explain the impact (or lack of impact) in this area? o Do water and sanitation interventions increase school attendance among children aged 7 to 12? And children age 6 to 18? What factors might explain the impact (or lack of impact) in this area?

Service, use, and sustainability o Were the water and sanitation projects implemented according to plan? o Are the results from the activity expected to be sustained over time? o Did the MCC investment reach intended/unintended beneficiaries?

Gender and social exclusion o Do the effect on health, education and access of water and sanitation interventions differ by gender or by expenditure levels (initial conditions)? o What factors (hygiene behavior, source and household-level water quality, household source choice) might explain the impact (or lack of impact) in a specific subpopulation?

The key to measuring the impacts caused by the water and sanitation interventions is to compare conditions with the interventions to conditions that would have prevailed without them. The counterfactual state is not naturally observable - we can never know what change would have occurred in program participants (the treatment group) if the program were not implemented. As it was not possible to apply randomization in the selection of water and sanitation projects in this case, the benefits of the water and sanitation projects will be measured with a rigorous quasi-experimental design that incorporates matching, pre- and post-implementation data collection, difference-in-difference estimation, and econometric analysis to estimate the counterfactual and address selection and other biases. This requires selecting a comparison group-households that are observationally similar to beneficiary households but do not participate in the program-and observing both sets of households before and after the program is implemented.

Matching represents a credible non-experimental option for identifying comparison groups. The evaluator uses propensity score matching (PSM) using data from the 2007 census to match the treatment communities to comparable communities before program implementation. PSM identifies comparison communities that have a similar probability of receiving the treatment and are similar to the treatment communities in terms of observable characteristics. Accordingly, they provide measures of indicators in communities that are similar except for the treatment; thus addressing selection on observables.

Geographic coverage

The survey was administered in the El Salvador Northern Zone departments of Cabañas, Chalatenango, Cuscatlán, La Unión, Morazán, San Miguel and Santa Ana.

Analysis unit

Census segments, households, individuals

Universe

Sixty-two municipalities in the Northern Zone, classified as either “Extrema Pobreza Moderada” or “Extrema Pobreza Alta” (extreme moderate poverty or extreme high poverty, respectively) by the national poverty map, were invited to submit proposals for water and sanitation projects. To be considered eligible for the program, the proposals had to meet four criteria: (1) the municipality had to be eligible to participate, meaning there were classified as high or moderate extreme poverty; (2) both the community and municipality had to be willing to make a financial/labor commitment to the project, (3) the community had to be organized and willing to work with the municipality, and (4) the estimated cost of the project could not exceed $850 per beneficiary. After projects that did not meet the eligibility criteria were excluded, a list of 68 projects remained. These were cleared to enter the feasibility stage. Comparisons segments were selected from non-beneficiary segments that where eligible to participate taking into account the poverty map, an proxies for financial capacity of the municipality and community involvement where included in the propensity score estimation.

Kind of data

Sample survey data [ssd]

Sampling procedure

In 2009, the evaluator recommended 18 observations per cluster and 164 communities, while adding an additional contingency -- 6 extra treatment segments and 6 extra control segments, for a total of 216 additional households in order to provide extra cushion for the loss of projects during implementation or inaccuracies in the sample frame. The final sample size for recommended for the study was 3,168, with 88 comparison and 88 treatment segments, each with 18 households.

However, in 2011, given changes to program design and required revisions to power calculations, the evaluator ultimately collected baseline data on 3,284 households, with 65 segments in both treatment and control and an average of 24-27 households per segment.

Research instrument

The household level survey is administered in the departments of Cabañas, Chalatenango, Cuscatlán, La Unión, Morazán, San Miguel and Santa Ana. The survey is composed of a set of sections to characterize the water access situation of households, household demographics, consumption, income/productive activities and time allocation of women and children.

The community level survey includes 130 census segments representing 196 caseríos. The information is obtained from interviews of key informants from the communities. Key informants include health workers/promoters, members of the water boards and other community leaders.

Response rate

94.5% for 2012 survey 96% for 2013 survey

description: Coastal communities are uniquely vulnerable to sea-level rise (SLR) and severe storms such as hurricanes. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms that could adversely affect the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey has developed the Sediment-Bound Contaminant Resiliency and Response (SCoRR) strategy to define baseline and post-event sediment-bound environmental health (EH) stressors. These data document the location, sampling techniques and field conditions observed while collecting soil and sediment samples from selected stations in the northeastern US during the 2015 pilot implementation of the SCoRR strategy. Photographs of sampling locations and conditions are also presented. Data in this release were collected during response mode.; abstract: Coastal communities are uniquely vulnerable to sea-level rise (SLR) and severe storms such as hurricanes. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms that could adversely affect the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey has developed the Sediment-Bound Contaminant Resiliency and Response (SCoRR) strategy to define baseline and post-event sediment-bound environmental health (EH) stressors. These data document the location, sampling techniques and field conditions observed while collecting soil and sediment samples from selected stations in the northeastern US during the 2015 pilot implementation of the SCoRR strategy. Photographs of sampling locations and conditions are also presented. Data in this release were collected during response mode.

This data release contains foreshore slopes for primarily open-ocean sandy beaches along the East Coast of the United States (Maine through Florida). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 1997 and 2018. The shoreline positions have been previously published, but the slopes have not. An along-shore reference baseline was defined, and then 20-meter spaced cross-shore beach transects were created perpendicular to the baseline. All data points within 1 meter (along-shore) of each transect were associated with that transect. For each transect, the points on the foreshore were identified, and a linear regression was fit through the foreshore points. Beach slope was defined as the slope of the regression. The regression was evaluated at the elevation of mean high water (MHW) to yield the cross-shore location of the shoreline. In areas where more than one lidar survey is available, the slopes from each survey are provi ...